CAL applies commutative algebra to build multi-scale localized descriptors for protein B-factor prediction, claiming 34.5% improvement over GNM on 364 proteins.
Persistent stanley–reisner theory.Foundations of Data Science, 8:287–312, 2026
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Commutative Algebra Learning for Protein Flexibility Analysis
CAL applies commutative algebra to build multi-scale localized descriptors for protein B-factor prediction, claiming 34.5% improvement over GNM on 364 proteins.